The development of AI technology is affecting the computer hardware industry through a subtle mechanism that is not obvious to the buyer unless he/she goes looking for a new PC, laptop, or memory expansion. The reason for this is the fact that artificial intelligence systems require immense computing power, and therefore, there is massive demand for chips and memory.
Artificial intelligence data centers require GPU and specialized processors; however, specialized processors also require immense memory capacity. Among the most popular memory for artificial intelligence applications is HBM or High Bandwidth Memory, which is designed for ultra-fast data transfer from memory to AI processors. As a result, the demand for HBM increases, forcing the memory producers to allocate their semiconductor manufacturing capacity in favor of AI-related products. Therefore, there is little space left for conventional DRAM production required by regular PCs, laptops, servers, and any other electronic equipment.
Thus, even non-AI computer memory might increase in price due to the competition between AI computers and regular ones in terms of access to semiconductors manufacturing capacity. According to TrendForce, the manufacturers of memory components maintained their focus on server and HBM products in 2026.
But there is pressure beyond just RAM. To build AI data centers, businesses require GPUs, complex processors, networking equipment, storage systems, power generation, and cooling technologies. All these products require considerable investments and demand is pressuring some sections of the semiconductor supply chain.
According to the International Energy Agency, investments made by five big technology companies exceeded $400 billion in 2025 and were expected to grow by 75% in 2026. Moreover, AI data-center electricity consumption grew faster than the total electricity consumption by all data centers.
And there is yet another issue: semiconductor fabs cannot just double their output immediately. Increasing production capacities takes years of time. According to Deloitte research published in July 2026, some additional memory capacity may emerge only in 2029 or even 2030.
This is how the effect can hit individual consumers. If producers of memory modules and other components have limited production capabilities, they will obviously give priority to products that are demanded more and cost more money. In such a way, prices for the hardware used in everyday computers will increase.
Thus, AI does not make every component of a regular computer expensive itself, but its demand is pressuring the same global hardware supply.
